Developments in image processing have made possible the processing of images in a variety of forms. A variety of filtering methods are available to improve the quality of images including brightness, contrast, non-blurring of edges in the images etc. Conventional available filters reduce impulse-type noise in an image. However, the removal of noise adversely affects edges or corners which exist in an image. The existing techniques while alleviating the noise excessively in the acquired image introduces a severe blurring effect in the discontinuity or edge portions. Also, the noise smoothening is insufficient because the images are low light conditioned images.
Few images are low light conditioned or low contrast type images. An example of such image is a retinal image obtained from a retinal camera. The imaging is plagued by poor visibility conditions due translucent nature of the several tissues exist in the anatomical structure of the retina in the human eye. This amounts to the problem of spatially varying reduction of contrast due to stray radiations, which are scattered by the tissue material. Additionally, the acquisition of image would suffer from impulsive type of noise, which is caused by malfunctioning pixels in camera sensors.
FIG. 1 illustrates an image acquired from a camera that is corrupted by impulsive noise due to camera sensor and low contrast. Conventional image filtering techniques apply noise smoothing filters with filter co-efficient either fixed or determined by some varying co-efficient that is governed by some error evaluation rule between updated output and desired output.
FIG. 2 illustrates the resultant image obtained by employing conventional noise smoothening processes. The conventional process enhances the image but at the same time, smoothens the edges and fails in enhancing the specially reduced contrast in the image due to scattered light. Thus the conventional process yields low contrast image. For purpose of understanding, a portion of image 202 has been highlighted in FIG. 2. In the highlighted portion 202, the image has become blur, and the lines are fainted due to smoothing of image. The highlighted portion 202 is just an exemplary embodiment, however the same effect can be seen over the entire image.
Therefore, the present disclosure overcomes the above-mentioned problems by providing system and methods for tackling both the impulsive noise occur in the retina image due to malfunction of camera sensor and image contrast enhancement that suffered due to low light visibility conditions